Division of Integrated Omics, Medical Research Center for High Depth Omics, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, 812-8582, Japan.
Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba, 277-8562, Japan.
Sci Rep. 2023 Mar 23;13(1):4758. doi: 10.1038/s41598-023-31547-2.
Interactions between various molecular species in biological phenomena give rise to numerous networks. The investigation of these networks, including their statistical and biochemical interactions, supports a deeper understanding of biological phenomena. The clustering of nodes associated with molecular species and enrichment analysis is frequently applied to examine the biological significance of such network structures. However, these methods focus on delineating the function of a node. As such, in-depth investigations of the edges, which are the connections between the nodes, are rarely explored. In the current study, we aimed to investigate the functions of the edges rather than the nodes. To accomplish this, for each network, we categorized the edges and defined the edge type based on their biological annotations. Subsequently, we used the edge type to compare the network structures of the metabolome and transcriptome in the livers of healthy (wild-type) and obese (ob/ob) mice following oral glucose administration (OGTT). The findings demonstrate that the edge type can facilitate the characterization of the state of a network structure, thereby reducing the information available through datasets containing the OGTT response in the metabolome and transcriptome.
生物现象中各种分子物种之间的相互作用产生了许多网络。研究这些网络,包括它们的统计和生化相互作用,可以帮助我们更深入地了解生物现象。节点与分子物种的聚类和富集分析经常被用来研究这些网络结构的生物学意义。然而,这些方法主要侧重于描述节点的功能。因此,很少有研究深入探讨节点之间的连接——边。在本研究中,我们旨在研究边的功能,而不是节点的功能。为此,对于每个网络,我们对边进行分类,并根据它们的生物学注释定义边的类型。然后,我们使用边的类型来比较健康(野生型)和肥胖(ob/ob)小鼠在口服葡萄糖耐量试验(OGTT)后肝脏的代谢组学和转录组学的网络结构。研究结果表明,边的类型可以帮助描述网络结构的状态,从而减少通过包含代谢组学和转录组学 OGTT 反应的数据集提供的信息。